Validating Antibodies for Specificity

Though an essential component of experimental design, negative controls are not implemented widely by antibody manufacturers and distributors. Neglecting this important validation step has resulted in the proliferation of nonspecific, poorly validated antibodies, thus contributing to a major problem in biomedicine: the reproducibility crisis.

The research community reportedly wastes an estimated $800 million every year on low-quality antibodies, and published research retractions over the past ten years have increased tenfold. By adopting negative controls as standard validation protocol, manufacturers, distributors, and individual labs working together can improve scientific reproducibility and accelerate the development of invaluable treatments.

This tutorial outlines a validation experiment using short interfering RNA (siRNA) knockdown, a powerful negative control method, and includes tips to optimize siRNA transfection experiments.

Genetic Methods Test Specificity

If an antibody is specific for its target, it should produce high signal in Western blot when the target is present and lower signal when the target’s abundance is diminished through genetic methods.

siRNA knockdown is one efficient method to diminish protein levels. It degrades messenger RNA (mRNA), inhibiting translation of the target protein. Figure 1 illustrates the difference between an siRNA-treated and untreated sample by Western blot for a specific AKT1 antibody. As shown, only the Hek 293 samples treated with AKT siRNA showed a diminished signal. When an antibody is nonspecific, signal will not be affected by siRNA.

Every scientist who works with antibodies should understand the knockdown strategy to interpret such data and perform knockdown validation in his or her own lab if antibodies have not been validated with negative controls.

Figure 1. Combination of siRNA-treated cells and a specific antibody results in a drop in signal compared to an untreated sample by Western blot.

Preparation and Experimental Design

Before starting your experiment, it is critical to create an RNase-free environment with an RNase-decontaminating solution. Additionally, it is recommended to use pipettes with RNase-free tips and avoid cross-contamination. Gloves are always used when working with siRNA and changed after touching any surface.

The knockdown experiment has three conditions: 1) the siRNA that targets the gene of interest, 2) a “scramble” siRNA—a construct with a random nucleotide sequence—controls for nonspecific changes in gene expression, and 3) a nontransfected positive control. When available, experimenters are recommended to include a second siRNA that targets the gene of interest to increase the rigor of the experiment. Fluorescent labeling of the siRNA clearly identifies the knockdown effect in cell culture.

Vector Design and Transfection

Efficient knockdown begins by transfecting a vector into the cell to generate siRNA. The vector contains the sequence needed to transcribe two, single-stranded 19–22mer DNA oligonucleotides linked at one end by a short-loop sequence, such as TTCAAGACG, that folds over and forms short hairpin RNA (shRNA), the precursor form of siRNA. Proteintech uses 21–23 nucleotide sequences with a guanine-cytosine (GC) content between 30 and 50 percent because it creates shRNA stable enough to form the hairpin shape but not too stable that it cannot be made into single-stranded RNA afterward.

Many online resources are available to assist with vector design for a chosen, target mRNA, including tools from RNAi Consortium, Dharmacon, Ui-Tei, and Genelink. A previously published siRNA sequence is also helpful to optimize knockdown of the target of interest as a positive control.

When working with a new target cell line, researchers should prepare to run multiple test transfections to optimize conditions. Cell culture conditions are kept constant throughout the experiment, with cell density kept close to 70%.

Successful transfection leads to transcription of the foreign DNA to generate the shRNA as described above and illustrated in Figure 2. Afterward, the enzyme Dicer removes the loop sequence in a process that transforms the shRNA into siRNA. The subsequent siRNA binds with RISC (RNA-induced silencing complex), dividing into two strands of RNA and activating the complex. RISC remains bound to one strand that binds complementarily to the target mRNA and degrades it, resulting in diminished production of the associated protein.

Figure 2. Successful transfection results in cells transcribing the foreign DNA to generate the shRNA, leading to diminished production of the target protein.

Evaluating Expression and Analysis

To generate the best results and ensure target specificity, researchers should titrate their transfections, generally using the lowest working concentration between 5–100 nM, or monitor protein levels and gene expression throughout the experiment using qPCR. Silencing mRNA usually generates observable effects after 24 hours, but can be longer if the turnover rate for the target protein is especially slow.

A successful knockdown validation assay downregulates the target gene in the knockdown sample and the signal correspondingly diminishes in a Western blot. Bands that are nonspecific or inconsistent across the whole Western blot membrane indicate that the antibody may be nonspecific. As a final step, researchers are urged to review the protocol and experimental design to ensure the conclusion reflects the antibody specificity and not an error in the experiment.

siRNA knockdown validation and similar negative controls, though requiring some additional time and expense for manufacturers and distributors, ensure the greatest confidence for antibody-generated data. Sometimes, though, validation with only positive controls is the only commercially available option. In these cases, researchers are urged to compile data from multiple published studies that cite the reagent catalog number and manufacturer and all available validation data from the manufacturers.

Higher antibody validation standards that include negative controls, such as siRNA knockdown, will increase the reproducibility of biomedical research, thereby improving the quality of scientific understanding and accelerating innovation.